BI: All content tagged as BI in NoSQL databases and polyglot persistence
Shaun Connolly (Hortonworks) lists the 3 most commons usages of Hadoop in a guest post on GigaOm:
- Data refinery
- Data exploration
- Application enrichment
Nothing new here, except the new buzzwords used to describe those Hadoop use cases that were slowly, but steadily establishing as patterns. And even if they sound nicer than ETL, analytics, etc. I doubt anyone needed new terms.
Original title and link: The three most common ways data junkies are using Hadoop ( ©myNoSQL)
Jay Kreps1 had a very interesting follow up to the GigaOM’s article Why big data might be more about automation than insights :
That article reminded me how immature people’s thinking about the use of data is. They are still thinking about “reports”. Reports indicate that that part of your business algorithm that is executed by a human. When you understand it well enough, whatever you are doing looking at a report a computer can do better and faster. But the real advantage is that computers can disaggregate decisions humans make into many many individual cases and be far more accurate.
The algorithms is:
- add instrumentation
- visualzie data
- turn visualization into a report
- automate reaction to report
- Wash, rinse, repeat.
Jay Kreps is working at LinkedIn in the SNA team. ↩
Original title and link: Reports Indicate That Part of Your Business Algorithm Is Executed by Humans ( ©myNoSQL)